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The present paper aims at earthquake prediction assessment in Iran using VLF radio signal sounding and space-based ULF emission observation. VLF subionospheric data using the Denizkoy transmitter in Turkey at 26.7 kHz and a receiving station in Tehran are incorporated. Three earthquake events during 2019 located at different distances to the signal propagation path are used in this study. The short-term variations in the VLF signal for the 5 days averaged amplitude, as well as the deviation of the VLF signal against the 30 days averaged signal to monitor the alternation in the trend, are employed in this study to perform earthquake prediction assessment using VLF radio signal sounding. Several characteristic parameters of the VLF signal such fall-time, minimum 1 and minimum 2 throughout the day are used. A threshold over the standard deviation of the signal is used to determine the signal anomaly. The signal anomalies associated with three selected events and the correlation of prediction with the distance are discussed. A decision-making procedure for the detection of EQ-related anomalies based on the assessment of the proposed approach is introduced. The ULF emissions recorded by the China Seismo-Electromagnetic Satellite (CSES) are provided and associated with the two analyzed earthquakes using the VLF data due to lack of time coverage for the third case. The space-based detected ULF signals are presented and discussed. The proximity of the detected ULF emission with respect to the earthquake epicenter is discussed.
Wydawca
Czasopismo
Rocznik
Tom
Strony
1269--1284
Opis fizyczny
Bibliogr. 36 poz.
Twórcy
autor
- Institute of Geophysics, University of Tehran, Tehran, Iran
autor
- Institute of Geophysics, University of Tehran, Tehran, Iran
autor
- Institute of Geophysics, University of Tehran, Tehran, Iran
Bibliografia
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Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-374df085-e718-4ada-beea-e55acd356af7